Re: [matplotlib-devel] trisurf plots with independent color data

[Geoffroy B. <geo...@gm...>]

Hi,

You can also try to pass a *color* array of size ntri (number of triangles)
to the *set_array* method of the collection returned by *plot_trisurf*.

See for instance:
http://stackoverflow.com/questions/24218543/colouring-the-surface-of-a-sphere-with-a-set-of-scalar-values-in-matplotlib/24229480#24229480



2015-01-21 17:02 GMT+01:00 Maximilian Albert <max...@gm...>:

> Hi Byron,
>
> This is a bit of a workaround, but you can specify facecolors explicitly
> by creating a triangulation of your surface explicitly and creating a
> Poly3DCollection with these facecolors. I'm attaching an example below
> which is a modified version of the plot_trisurf demo [1] in the matplotlib
> documentation. It showcases both random colors and a smooth gradient (the
> latter in the line that's commented out).
>
> I would have thought that it should be possible to pass an argument like
> "facecolors" to plot_trisurf directly, since the documentation [2] states
> that "other arguments are passed on to Poly3DCollection". However, I
> couldn't get this to work quickly. Maybe someone else knows how?
>
> Best regards,
> Max
>
> [1] http://matplotlib.org/examples/mplot3d/trisurf3d_demo.html
> [2] http://matplotlib.org/mpl_toolkits/mplot3d/api.html
>
>
>
> from mpl_toolkits.mplot3d import Axes3D
> from matplotlib import cm
> import matplotlib.pyplot as plt
> import numpy as np
>
> from matplotlib.tri import Triangulation
> from mpl_toolkits.mplot3d.art3d import Poly3DCollection
>
> n_angles = 36
> n_radii = 8
>
> # An array of radii
> # Does not include radius r=0, this is to eliminate duplicate points
> radii = np.linspace(0.125, 1.0, n_radii)
>
> # An array of angles
> angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
>
> # Repeat all angles for each radius
> angles = np.repeat(angles[...,np.newaxis], n_radii, axis=1)
>
> # Convert polar (radii, angles) coords to cartesian (x, y) coords
> # (0, 0) is added here. There are no duplicate points in the (x, y) plane
> x = np.append(0, (radii*np.cos(angles)).flatten())
> y = np.append(0, (radii*np.sin(angles)).flatten())
>
> # Pringle surface
> z = np.sin(-x*y)
>
> tri = Triangulation(x, y)  # NOTE: This assumes that there is a nice
> projection of the surface into the x/y-plane!
> triangle_vertices = np.array([np.array([[x[T[0]], y[T[0]], z[T[0]]],
>                                         [x[T[1]], y[T[1]], z[T[1]]],
>                                         [x[T[2]], y[T[2]], z[T[2]]]]) for
> T in tri.triangles])
> midpoints = np.average(triangle_vertices, axis=1)
>
> def find_color_for_point(pt):
>     x, y, z = pt
>     col = [(y+1)/2, (1-y)/2, 0]
>     return col
>
> #facecolors = [find_color_for_point(pt) for pt in midpoints]  # smooth
> gradient
> facecolors = [np.random.random(3) for pt in midpoints]  # random colors
>
> coll = Poly3DCollection(triangle_vertices, facecolors=facecolors,
> edgecolors='black')
>
> fig = plt.figure()
> ax = fig.gca(projection='3d')
> ax.add_collection(coll)
> ax.set_xlim(-1, 1)
> ax.set_ylim(-1, 1)
> ax.set_zlim(-1, 1)
> ax.elev = 50
>
> plt.show()
>
>
>
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